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Abstract

This chapter outlines recent ABS research in applying data visualisation to the analysis of big data for official statistics. Examples are presented from the application of a prototype analytical platform created by the ABS to two significant big data use cases. This platform – the Graphically Linked Information Discovery Environment (GLIDE) – demonstrates a new approach to representing, integrating and exploring complex information from diverse sources. This chapter discusses the role of data visualisation in meeting the analytical challenges of big data and describes the entity-relationship network model and data visualisation features implemented in GLIDE, together with examples drawn from two recent projects. It concludes and outlines future directions.

Role Of Data Visualisation

Big data offers fresh analytical insights for policy development, regulatory compliance and service delivery, particularly when combined in a problem-specific way with survey and administrative data sets. This is of particular value to governments in tackling “wicked problems” (APSC, 2012), such as indigenous disadvantage, obesity, climate change, and land degradation. Wicked problems are intrinsically complex, dynamic and difficult to objectively define – they are characterised by many contributing time-dependent factors of varying effect that interact in subtle and sometimes surprising ways. To identify the important causal factors and understand their interactions over time, analysis needs to incorporate diverse economic, demographic, social and environmental data, and to move iteratively between the exploration and explanation of data.